This post is maintained by Bytebase, an open-source database DevSecOps tool that can manage both Oracle and PostgreSQL. We update the post every year.
| Update History | Comment |
|---|---|
| 2025/04/25 | Initial version. |
Oracle and PostgreSQL are two leading relational database management systems with distinct approaches. Oracle, developed by Oracle Corporation, is a commercial enterprise-grade database known for robust features and reliability but comes with significant licensing costs. PostgreSQL is a powerful open-source alternative offering advanced features, standards compliance, and extensibility without licensing fees.
This comparison examines their architectures, features, performance, licensing models, and use cases to help technical professionals and business decision-makers understand their strengths and limitations.
History and Background
Oracle Database began in 1977 when Larry Ellison, Bob Miner, and Ed Oates created the first commercial SQL-based RDBMS, released as Oracle V2 in 1979. Key developments include Oracle7 (1992) with improved performance, Oracle8i (1999) with Java support, Oracle10g (2003) with grid computing, Oracle12c (2013) with multitenant architecture, and Oracle19c (2019), the current long-term support release. Oracle is developed and maintained by Oracle Corporation, driven by commercial interests and enterprise requirements.
PostgreSQL originated from the POSTGRES project at UC Berkeley in the mid-1980s under Professor Michael Stonebraker. It evolved into PostgreSQL in 1996, adding SQL support to its ability to handle complex data types and user-defined functions. Major releases include PostgreSQL 8.0 (2005) with Windows support, 9.0 (2010) with built-in replication, and 16 (2023) with enhanced performance and security. Unlike Oracle, PostgreSQL is developed by a global community through the PostgreSQL Global Development Group, prioritizing standards compliance and extensibility while remaining free and open-source.
Comparison Summary
| Oracle | PostgreSQL | |
|---|---|---|
| Architecture | Complex, enterprise-focused | Simpler, more straightforward |
| Licensing | Commercial, expensive ($47,500+ per core) | Free, open-source (PostgreSQL License) |
| Community Support | Commercial support | Active open-source community |
| Data Types | Standard with some advanced types | Extensive with better JSON support |
| Extensibility | Limited | Highly extensible |
| SQL Compliance | Partial with proprietary extensions | Strong standards compliance |
| Scalability | Excellent with RAC for horizontal scaling | Good, relies on third-party solutions for clustering |
| High Availability | Built-in with RAC and Data Guard | Available through third-party tools |
| Security Features | Comprehensive enterprise security | Strong basic security, extensible |
| Performance (OLTP) | Superior for very large workloads | Excellent for most common workloads |
| Performance (Analytics) | Excellent with specialized features | Good, improving with recent versions |
| Admin (Install) | Complex and resource-intensive | Simple and straightforward |
| Admin (Day-to-Day) | Comprehensive built-in tools | Manual configurations and third-party tools |
| Admin (Monitoring) | Extensive built-in tools | Basic with extensions |
| Cloud Offerings | Oracle Cloud (expensive but feature-rich) | Available on all major cloud platforms (cost-effective) |
| Cost (16 cores) | ~$760,000 + $167,200/year support | $0 (licensing) |
| Cloud Cost (2vCPU) | $400-500/month | $115-150/month |
| Best For | Mission-critical enterprise applications | Web applications, startups, cost-sensitive deployments |
Detailed Comparison
Architecture
Oracle: Enterprise-grade with many specialized components:
-
Memory:
- SGA: Shared cache and SQL execution
- PGA: Per-process memory
- Includes buffer cache, shared pool, large pool, etc.
-
Processes:
- Server processes handle user queries
- Background: DB Writer, Log Writer, Checkpoint, SMON (recovery), PMON (cleanup), Archiver
-
Storage:
- Control files, datafiles, redo/archived logs, parameter and log files
-
Logical Structure:
- Tablespaces > Segments > Extents > Blocks
PostgreSQL: Simpler, open-source architecture:
-
Processes:
- Postmaster manages the server
- One backend per connection
- Background tasks: Writer, Checkpointer, Autovacuum, WAL Writer, Logger
-
Memory:
- Shared buffers, WAL buffers, work memory, maintenance memory
-
Storage:
- Data directory with
base,global,pg_wal - Config files:
postgresql.conf,pg_hba.conf
- Data directory with
-
Logical Structure:
- Databases > Schemas > Tables > Indexes
Licensing and Cost Structure
Oracle offers multiple editions with different pricing and licensing models:
-
Enterprise Edition (EE):
- Full features (security, performance, HA)
- ~$47,500 per processor core or $950 per named user (min 25 users)
- Add-ons (e.g., RAC, In-Memory, Data Guard) cost extra
-
Standard Edition 2 (SE2):
- For smaller setups, limited to 2 sockets
- ~$17,500 per socket or $350 per named user (min 10 users)
- No optional features
-
Express Edition (XE):
- Free, with limitations: 2 CPU threads, 2GB RAM, 12GB data
- For dev or lightweight apps
-
Personal Edition:
- For single-user development
- Priced similar to SE2
-
Additional Costs:
- Annual support (~22% of license cost)
- Management packs, engineered systems (e.g., Exadata)
PostgreSQL uses a simple, open-source license:
-
License: PostgreSQL License (MIT/BSD-style)
-
Cost: Free for any use — no fees, limits, or user restrictions
-
Commercial Use: Fully permitted, including embedding in proprietary apps
-
Potential Costs:
- Infrastructure (cloud/on-prem)
- Optional support or consulting
- Paid third-party tools
Example: 16-core deployment
| Platform | License Cost | Annual Support | Total (Year 1) |
|---|---|---|---|
| Oracle EE | ~$760,000 | ~$167,200 | ~$927,200 |
| Oracle SE2 | Not suitable | — | — |
| PostgreSQL | $0 | Optional | ~$0 |
Managed Cloud Pricing (2 vCPU, 8 GB RAM, 100 GB storage):
- AWS RDS for Oracle EE: ~$400–500/month
- AWS RDS for PostgreSQL: ~$141/month
- Azure Database for PostgreSQL: ~$141/month
- Google Cloud SQL for PostgreSQL: ~$117/month
Data Types and Extensibility
| Feature | Oracle | PostgreSQL |
|---|---|---|
| Standard SQL types | ✅ | ✅ |
| JSON support | Limited (improving in recent versions) | ✅ Native JSON and JSONB |
| XML support | ✅ XMLType | ✅ Native support |
| Spatial types | ✅ Oracle Spatial | ✅ Built-in with PostGIS |
| Geometric types | ❌ | ✅ POINT, LINE, POLYGON |
| Network address types | ❌ | ✅ INET, CIDR |
| Array types | ❌ | ✅ Native ARRAY type |
| Range types (e.g., date/number) | ❌ | ✅ Built-in support |
| Object types / UDTs | ✅ With limitations | ✅ Fully supported with CREATE TYPE |
| Extensible type system | ⚠️ Limited | ✅ Highly extensible, supports custom data types |
PostgreSQL stands out for its rich and extensible type system, offering superior support for modern formats and complex data modeling.
SQL Compliance and Extensions
| Feature | Oracle | PostgreSQL |
|---|---|---|
| SQL Standard Compliance | Partial, many proprietary extensions | Strong compliance |
| Procedural Language | PL/SQL | PL/pgSQL |
| Recursive Queries | CONNECT BY (proprietary syntax) | Standard CTEs with WITH RECURSIVE |
| Window Functions | ✅ | ✅ |
| Materialized Views | ✅ | ✅ |
| Full-text Search | ❌ | ✅ Built-in support |
| Syntax Style | Oracle-specific | Standards-compliant |
PostgreSQL is more aligned with SQL standards, while Oracle offers powerful but proprietary features.
Indexing Capabilities
| Feature | Oracle | PostgreSQL |
|---|---|---|
| B-tree indexes | ✅ Default | ✅ Default |
| Bitmap indexes | ✅ | ❌ |
| Hash indexes | ❌ | ✅ |
| Function/Expression indexes | ✅ Function-based | ✅ Expression-based |
| Partial indexes | ⚠️ Via function-based indexes | ✅ Native support |
| Domain indexes | ✅ For custom data types | ⚠️ Limited (via extensions or functional workarounds) |
| Full-text indexes | ✅ Oracle Text | ✅ GIN/GiST with tsvector |
| GiST indexes | ❌ | ✅ Generalized Search Tree |
| SP-GiST indexes | ❌ | ✅ Space-partitioned GiST |
| GIN indexes | ❌ | ✅ Generalized Inverted Index |
| BRIN indexes | ❌ | ✅ Block Range Index |
| Custom index types | ⚠️ Limited | ✅ Fully extensible |
PostgreSQL provides a richer variety of index types, making it more suitable for advanced and specialized querying scenarios.
Concurrency and Transactions
| Feature | Oracle | PostgreSQL |
|---|---|---|
| MVCC (Multi-Version Concurrency) | ✅ | ✅ |
| Read consistency level | Statement-level | Transaction-level |
| Row-level locking | ✅ | ✅ |
| Isolation levels | Read Committed, Serializable | Read Committed, Repeatable Read, Serializable |
| Distributed transactions | ✅ Two-phase commit | ✅ Two-phase commit |
| Autonomous transactions | ✅ | ❌ |
| Advisory locks | ❌ | ✅ Application-controlled locking |
Both support strong transactional guarantees, but PostgreSQL offers finer control over isolation and application-level locking, while Oracle uniquely supports autonomous transactions.
High Availability and Replication
| Feature | Oracle | PostgreSQL |
|---|---|---|
| Clustering | ✅ Real Application Clusters (RAC) | ❌ No built-in clustering (use Patroni, Stolon, etc.) |
| Physical replication | ✅ Data Guard | ✅ Streaming replication |
| Readable standby | ✅ Active Data Guard | ✅ With streaming replication (hot standby) |
| Logical replication | ✅ Golden Gate | ✅ Built-in since v10 |
| Synchronous replication | ✅ | ✅ |
| Asynchronous replication | ✅ | ✅ |
| Point-in-time recovery | ✅ Flashback Database | ✅ Built-in PITR support |
| Transparent failover | ✅ Application Continuity | ⚠️ Requires external tooling |
| Connection pooling | ⚠️ App-dependent | ✅ Via pgBouncer or Pgpool-II |
Oracle provides more integrated, enterprise-grade HA options like RAC and Application Continuity. PostgreSQL achieves similar goals with flexibility and third-party tooling.
Performance Features
| Feature | Oracle | PostgreSQL |
|---|---|---|
| Result cache | ✅ Query + PL/SQL function result cache | ❌ |
| In-Memory Column Store | ✅ | ❌ (can use extensions like Citus or TimescaleDB) |
| Automatic memory management | ✅ | ⚠️ Manual tuning required |
| Parallel query execution | ✅ | ✅ (limited but improving) |
| Partitioning | ✅ Range, list, hash, composite | ✅ Range, list, hash |
| Just-in-time (JIT) compilation | ❌ | ✅ |
| Table/index statistics | ✅ | ✅ |
| SQL optimization / tuning | ✅ Auto SQL tuning, SQL Plan Management | ✅ Cost-based optimizer |
| Query plan visualization | ✅ | ✅ EXPLAIN ANALYZE and visualization tools |
| Workload/resource management | ✅ Resource Manager | ⚠️ Requires manual management or third-party tools |
| Connection pooling | ⚠️ App-dependent | ✅ Via pgBouncer, Pgpool-II |
| External data access | ✅ Oracle Gateway | ✅ Foreign Data Wrappers (FDW) |
Oracle offers more built-in, enterprise-grade performance features for large workloads. PostgreSQL covers most essentials and continues to improve, especially in recent versions.
OLTP Workloads (Performance)
| Feature | Oracle | PostgreSQL |
|---|---|---|
| OLTP optimization | ✅ High-throughput, low-latency | ✅ Good for typical workloads |
| Concurrency handling | ✅ Advanced, predictable under load | ✅ Efficient MVCC, improving concurrency |
| In-memory data support | ✅ In-Memory Column Store | ❌ (extensions available) |
| Result caching | ✅ | ❌ |
| Query optimization | ✅ Sophisticated optimizer | ✅ Cost-based, performant for simple queries |
| Performance at scale | ✅ Excellent | ⚠️ May need tuning for very high volumes |
Oracle excels in high-volume OLTP; PostgreSQL performs well with tuning and is suitable for most transactional workloads.
Analytical Workloads (Performance)
| Feature | Oracle | PostgreSQL |
|---|---|---|
| Parallel query execution | ✅ | ✅ |
| Bitmap indexes | ✅ | ❌ |
| Star query optimization | ✅ | ❌ |
| Materialized views | ✅ With query rewrite | ✅ Manual refresh |
| Partitioning | ✅ Mature, multiple strategies | ✅ Improved in recent versions |
| In-memory analytics | ✅ In-Memory Column Store | ❌ |
| Semi-structured data support | ⚠️ JSON support (limited) | ✅ JSONB for analytics |
| External data integration | ✅ Oracle Gateway | ✅ Foreign Data Wrappers |
| Time-series data support | ❌ | ✅ With TimescaleDB extension |
Oracle leads in large-scale analytics; PostgreSQL is increasingly capable, especially with extensions.
Benchmark Comparisons (Performance)
Oracle Database Appliance X9-2-HA:
- Transactions per second (TPS): Over 35,000 TPS with 32 CPU cores per node
- Average transaction response time: Less than 12.1 ms
PostgreSQL (Managed Cloud Services):
| Platform | Transactions/sec (TPS) | Avg. Latency (ms) |
|---|---|---|
| AWS RDS for PostgreSQL | ~2,700 | ~2.88 |
| Azure Database for PostgreSQL | ~2,400 | ~3.26 |
| Google Cloud SQL for PostgreSQL | ~1,300 | ~5.74 |
| Supabase PostgreSQL | ~1,600 | ~5.10 |
- Oracle demonstrates superior performance in high-throughput environments, particularly with optimized hardware configurations.
- PostgreSQL offers solid performance for most workloads, with the added benefit of lower operational costs.
Security Features
| Feature | Oracle | PostgreSQL |
|---|---|---|
| Row-level security | ✅ VPD (Virtual Private Database) | ✅ Native policies |
| Multi-level security | ✅ Label Security | ❌ |
| Separation of duties | ✅ Database Vault | ⚠️ Manual role management |
| Data encryption at rest | ✅ Transparent Data Encryption (TDE) | ⚠️ Filesystem-level encryption |
| Column-level data masking | ✅ Data Redaction | ⚠️ Requires custom implementation or extensions |
| Column-level privileges | ✅ | ✅ |
| Role-based access control | ✅ | ✅ |
| SSL/TLS encryption | ✅ | ✅ |
| External authentication | ✅ Enterprise User Security (LDAP, Kerberos) | ✅ LDAP, GSSAPI |
| Audit logging | ✅ Built-in, comprehensive | ⚠️ Via extensions like pgaudit |
| Privilege analysis | ✅ | ❌ |
Oracle delivers more out-of-the-box security tools suited for strict compliance and enterprise use. PostgreSQL meets most core needs, with extensions filling advanced gaps.
Bytebase provides column-level dynamic data masking to Postgres.
Installation and Setup (Administration)
| Feature | Oracle | PostgreSQL |
|---|---|---|
| Installation complexity | ❌ Complex, multiple components and configurations | ✅ Simple, package managers available (apt, yum, etc.) |
| Disk space requirements | ❌ High (minimum ~6.8 GB) | ✅ Low (varies by platform) |
| Pre-installation requirements | ❌ Detailed prerequisites (users, kernel parameters, etc.) | ✅ Minimal prerequisites |
| Installation tools | ✅ Oracle Universal Installer | ✅ Native installers, Docker containers |
| Configuration options | ✅ Extensive | ⚠️ Fewer initial options, can be configured post-installation |
Oracle's installation is more complex and resource-intensive, while PostgreSQL offers a simpler and more straightforward setup process.
Day-to-Day Operation (Administration)
| Feature | Oracle | PostgreSQL |
|---|---|---|
| Graphical administration tools | ✅ Enterprise Manager | ✅ pgAdmin |
| Command-line tools | ✅ SQL*Plus, SQLcl | ✅ psql |
| Memory management | ✅ Automatic | ⚠️ Manual tuning required |
| Storage management | ✅ Automatic Storage Management (ASM) | ⚠️ Manual configuration |
| Performance monitoring | ✅ Automatic Workload Repository (AWR) | ⚠️ Extensions like pg_stat_statements |
| Workload management | ✅ Database Resource Manager | ⚠️ Manual or third-party tools |
| Backup and recovery | ⚠️ Complex procedures | ✅ Simple tools (pg_dump, pg_restore) |
Oracle provides comprehensive built-in tools for administration, while PostgreSQL relies more on manual configurations and third-party tools.
Monitoring and Diagnostics (Administration)
| Feature | Oracle | PostgreSQL |
|---|---|---|
| Diagnostic repository | ✅ Automatic Diagnostic Repository (ADR) | ❌ Not available |
| Performance data collection | ✅ Automatic Workload Repository (AWR) | ⚠️ Extensions like pg_stat_statements |
| Session history | ✅ Active Session History (ASH) | ❌ Not available |
| Query monitoring | ✅ SQL Monitoring | ⚠️ Manual analysis using EXPLAIN ANALYZE |
| Graphical dashboards | ✅ Enterprise Manager | ⚠️ Third-party tools (e.g., pgAdmin, pganalyze) |
| Log and trace files | ✅ Alert logs, trace files | ✅ Log files |
| Dynamic performance views | ✅ V$ views | ✅ pg_stat_* views |
Oracle offers extensive built-in monitoring and diagnostic tools, whereas PostgreSQL provides basic capabilities with the option to enhance via extensions and third-party tools.
Cloud Offerings Comparison
Oracle Cloud
Oracle Autonomous Database
- Fully managed (self-tuning, patching, scaling)
- Supports OLTP and analytics workloads
- Estimated cost: $1,500–$2,000/month for 2 vCPU, 8GB RAM, 100GB storage
Oracle Database Cloud Service
- Manually managed with configurable service levels
- Estimated cost: $800–$1,200/month
PostgreSQL Managed Services
AWS RDS for PostgreSQL
- Fully managed with Multi-AZ support, automatic backups
- Performance: ~2,700 TPS, 2.88 ms latency
- Cost: $141.44/month
Azure Database for PostgreSQL
- Flexible Server with high availability
- Performance: ~2,400 TPS, 3.26 ms latency
- Cost: $141.44/month
Google Cloud SQL for PostgreSQL
- Fully managed with automated maintenance
- Performance: ~1,300 TPS, 5.74 ms latency
- Cost: $116.70/month
Other Providers
- Supabase, Heroku, DigitalOcean, Aiven, Amazon Aurora (PostgreSQL-compatible)
Cost Comparison (2 vCPU, 8GB RAM, 100GB Storage)
| Provider | Monthly Cost | Notes |
|---|---|---|
| Oracle Autonomous Database | $1,500–$2,000 | Advanced features, automation |
| Oracle Database Cloud Service | $800–$1,200 | Manual setup and management |
| AWS RDS for PostgreSQL | $141.44 | High performance, fully managed |
| Azure Database for PostgreSQL | $141.44 | Flexible config, high availability |
| Google Cloud SQL for PostgreSQL | $116.70 | Lower cost, higher latency |
Note: Prices are approximate and may vary by region and usage.
Oracle offers rich enterprise features at a premium price. PostgreSQL cloud services provide a cost-effective, flexible alternative with solid performance.
Use Cases and Industry Adoption
Oracle Best for:
- Large enterprise apps (ERP, CRM, finance)
- Mission-critical systems (banking, telecom, healthcare)
- Massive data warehouses and real-time analytics
- High-volume OLTP (trading, reservations, e-commerce)
Common Users: Fortune 500 companies, Major banks & government agencies, Large healthcare and telecom providers
PostgreSQL Best for:
- Web & SaaS applications
- Geospatial apps (with PostGIS)
- Development and CI/CD environments
- Budget-conscious use (startups, education, non-profits)
- Mixed-data apps (JSON, XML, custom types)
Common Users: Apple, Instagram, Spotify, Reddit, Netflix, U.S. FAA and many tech startups
Conclusion
Oracle excels in enterprise environments where budget is not a constraint and maximum reliability is required. It's ideal for mission-critical applications, large-scale data warehousing, and scenarios requiring comprehensive enterprise features out-of-the-box.
PostgreSQL shines in modern applications, cost-sensitive deployments, and scenarios requiring flexibility and extensibility. It's perfect for web applications, startups, and projects that benefit from its modern features and active community.
